Taylor-Fourier PMU on a Real-Time Simulator: Design, Implementation and Characterization

Abstract

The development of software models of Phasor Measurement Units (PMUs) within Real-Time Simulators (RTSs) represents a promising tool for the design and validation of monitoring and control applications in electrical power networks. In this sense, it is necessary to find an optimal trade-off between computational complexity and estimation accuracy. In this paper, we present the design and implementation of two new PMU models within the Opal-RT eMEGAsim RTS. The synchrophasor estimation algorithm relies on a Compressive Sensing Taylor-Fourier Model (CS-TFM) approach, and enables us to extract the dynamic phasor associated to the signal fundamental component. The estimation accuracy of the proposed models is characterized with respect to the compliance tests of the IEEE Std. C37.118.1.

Review of PMU Algorithms Suitable for Real-Time Operation With Digital Sampled Value Data

“…Experimentally, the amplitude and phase estimation together with their respective derivatives, are performed every 2 signal cycles. This algorithm has been modified in [24] and optimised for real-time operation. Calculations are performed over a 3-cycle and 5-cycle measurement windows for P class and M class PMUs, so not on a sample per sample basis.…”

Impact of Synchrophasor Estimation Algorithms in ROCOF-Based Under-Frequency Load-Shedding

“…For each synchrophasor estimation algorithm, we develop a dedicated PMU model to be deployed in every load bus [44], [45]. The considered power grid as well as the measurement devices are modelled in MATLAB Simulink and executed [30].…”

“…d) Phasor Measurement Units: In this paper, we compare the accuracy provided by two different ROCOF estimation techniques, based on consolidated state-of-the-art algorithms like e-IpDFT [27] and cs-TFM [28]. The details regarding their implementation within the adopted RTS are provided in [44] and [45], respectively.…”

“…The spectral analysis can be limited to the expected variation range of the fundamental component, i.e. [45,55] Hz. As shown in Algorithm 3, the first step consists in enhancing the frequency resolution by projecting X over the vector space spanned by matrix D f .…”

On the Importance of Characterizing Virtual PMUs for Hardware-in-the-Loop and Digital Twin Applications

“…For example, [39] described a PMU-RTS HIL test bed that aims at characterizing physical PMUs. In [40][41][42], virtual PMUs have been developed and implemented inside a DT environment. Complete DT infrastructure consisting of physical PMUs and RTS-based simulation systems has been described in [43][44][45].…”